the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Oct 2024
Technical Note: Benchmark time-temperature paths provide a shared framework for evaluating and communicating thermochronologic data interpretation
Abstract. We present a set of six time-temperature (tT) histories, called benchmark paths, that can be used as a shared framework for evaluating the sensitivity of a thermochronologic system to the variables inherent in the interpretation of thermochronologic data (e.g., kinetics models, mineral compositions or geometries, etc.). These benchmark paths span 100 Myr, include monotonic and nonmonotonic histories that represent plausible geologic scenarios, and have a range of cooling rates through different chronometer partial-retention/annealing temperatures. Here, we demonstrate their utility by presenting a method for tuning these paths to 11 different kinetics models for the apatite (U-Th-Sm)/He (n=5), apatite fission-track (n=2), and zircon (U-Th)/He (n=4) systems. These tuned tT paths provide a practical comparison of the kinetics models for each system and the data patterns they predict, thereby offering anyone performing thermal history analysis the ability to consider how their choice of kinetics model may impact their data interpretation. The adoption of benchmark paths for evaluating kinetics models and other variables provides a practical way for the thermochronology community to evaluate and communicate the decision making processes that are inherent in thermochronologic modeling and data interpretation.
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RC1: 'Comment on gchron-2024-20', Anonymous Referee #1, 17 Oct 2024
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Goddard et al. present six time-temperature (t-T) paths that represent "plausible geologic scenarios" for evaluating the sensitivity of different thermochronologic systems, ultimately to be used in evaluating and communicating data interpretations.
The following questions could be asked:
1. Is there a need/is it a good idea to standardize t-T benchmark curves?
2. Is the proposed selection of t-T benchmarks fit for purpose?
3. Should the authors make this decision on behalf of the thermochronology community?These questions are addressed in order below.
1. I do not think there is a need, nor is it a good idea, to "standardize" t-T curves. I’m not sure of the exact reason for doing this either? Many if not all of the t-T curves are those published [or variations thereof] in Wolf et al. (1998), which were also discussed in the recent Murray et al. (2022) HeFTy modeling summary paper (their Figures 2 and 3). So it isn’t clear to me what is new in the manuscript other than the proposal to include this information more formally/separately in the GChron 'special issue’ on interpretation/modeling. The authors do expand the applied thermochronometers beyond apatite (U-Th)/He and fission track (in Wolf et al.) to include zircon (U-Th)/He, but this does not justify a new contribution. Beyond this, the predicted data from such "benchmark" t-T paths can be generated by anyone wanting to examine those histories on their own and refer to the original Wolf et al. work, just like the author's did in their 2022 Geosphere publication.As stated in Lines 63–70 of the manuscript: "We demonstrate the utility of our proposed benchmark paths by using them to illustrate the different temperature sensitivities of three low-temperature thermochronometers (AHe, AFT, ZHe), and then, within each system, how kinetics models also require different temperatures to produce the same age. This is useful because although experimentally-derived kinetics models provide the foundation for the interpretation of thermochronologic data, it can be difficult to develop a practical understanding of if or how choosing one kinetics model over another might impact one’s thermal history model results. This is critical for both project design and data interpretation." (italics added here)...and stated in Lines 217–225, Section 5: "A vision for the application of benchmark paths. Here, we demonstrate how a suite of benchmark tT paths can be designed to leverage the temperature sensitivity of a particular low-temperature thermochronometer and then tuned to specific kinetics models. We propose that the six benchmark paths we use in this work can provide a practical tool for the thermochronology community to use in a variety of contexts, including comparing kinetics models and predicting data patterns that arise from variable mineral compositions or geometries. This ‘design-then-tune’ approach is not meant to identify a single ‘best’ kinetics model for a particular system but to quantify and visualize how kinetics models predict different tT conditions and data patterns." (italics added here)This is simply forward modeling a t-T path and extracting the predicted data—one of the most fundamental things we do. What is being tuned? I think it is generally understood that kinetic models will produce different predictions, or so-called 'data patterns'. Kinetic models do not strictly predict "different tT conditions" but in this case instead yield model ages under a specified t-T condition. Furthermore, all of the identified kinetic models for (U-Th)/He and fission track have flaws and varying degrees of uncertainty, with many of the uncertainties and/or assumptions being different between models for the same system (e.g., different AFT analysts and compositional data/quantities considered in Ketcham et al. 1999 v. 2007 kinetic models). The same path producing slightly different age predictions is inherent to such differences in kinetic models. More often than not, kinetic models are a progression in understanding and improved calibration. Therefore, the answer may be that the most recent kinetic model is the preferable one, unless there is a specific reason for choosing otherwise (i.e., different fundamental radiation damage assumptions between Guenthner v. Ginster in zircon). For example, no one is going to try to publish t-T models using the original Wolf '96/Farley '00 helium diffusion kinetics that do not account for radiation damage. In terms of how choice of kinetics impacts t-T model results, there a number of papers that already show these sorts of effects (e.g., Guenthner 2021). In light of this, showing the effects again here for "benchmark" paths does not seem particularly useful given the near infinite number of t-T histories that could be also considered a benchmark by another modeler. I could see this sort of exercise being useful for training students or for use as a module in an university course. However, it would be better implemented as an activity and not reading material.2. I would say that the answer to this question is debatable. There are many t-T paths that could considered representative benchmarks, and that could be argued in different ways and mostly depends on perspective and context. Due to those reasons alone, one could perhaps argue that “standardization” is necessary, but I would actually think the opposite. Why were these particular paths chosen, are they truly representative of end member geological environments, or is it simply because they exist? The t-T paths presented in the manuscript were conjured in the original Wolf et al. publication but that doesn't mean that those t-T paths are special in any meaningful way.3. If something like this were to be done it would require broader input as to the reasons why this is necessary and what the very specific usage of such standardized paths would actually be. I do not think this sort of standardization is useful or beneficial on behalf of the community and could actually generate confusion going forward if someone shows a certain t-T path as an example and they are instead “told” to use one of these “benchmark” histories. Again, a similar exercise can be done by anyone modeling 'real world' data to get an understanding of the sensitivity across different thermochronometric mineral systems with respect to a proposal history.References:Farley, K. A.: Helium diffusion from apatite: General behavior as illustrated by Durango fluorapatite, J. Geophys. Res. Solid Earth, 105, 2903–2914, https://doi.org/10.1029/1999jb900348, 2000.Guenthner, W. R.: Implementation of an Alpha Damage Annealing Model for Zircon (U‐Th)/He Thermochronology With Comparison to a Zircon Fission Track Annealing Model, Geochemistry, Geophys. Geosystems, 22, https://doi.org/10.1029/2019GC008757, 2021.Ketcham, R. A., Donelick, R. A., and Carlson, W. D.: Variability of apatite fission-track annealing kinetics: III. Extrapolation to geological time scales, Am. Mineral., 84, 1235–1255, https://doi.org/10.2138/am-1999-0903, 1999.Ketcham, R. A., Carter, A., Donelick, R. A., Barbarand, J., and Hurford, A. J.: Improved modeling of fission-track annealing in apatite, Am. Mineral., 92, 799–810, https://doi.org/10.2138/am.2007.2281, 2007.Murray, K. E., Goddard, A. L. S., Abbey, A. L., and Wildman, M.: Thermal history modeling techniques and interpretation strategies: Applications using HeFTy, Geosphere, 18, 1622–1642, https://doi.org/10.1130/GES02500.1, 2022.Wolf, R. A., Farley, K. A., and Silver, L. T.: Helium diffusion and low-temperature thermochronometry of apatite, Geochim. Cosmochim. Acta, 60, 4231–4240, https://doi.org/10.1016/S0016-7037(96)00192-5, 1996.Wolf, R. A., Farley, K. A., and Kass, D. M.: Modeling of the temperature sensitivity of the apatite (U-Th)/He thermochronometer, Chem. Geol., 148, 105–114, https://doi.org/10.1016/S0009-2541(98)00024-2, 1998.Citation: https://doi.org/10.5194/gchron-2024-20-RC1 -
RC2: 'Comment on gchron-2024-20', Anonymous Referee #2, 18 Oct 2024
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Why do we need new benchmarks? I don’t think this short paper has made a strong case. Tellingly, in the discussion (lines 227-232) authors note that ..”a single suite of tuned paths cannot capture all complexities of these systems”……. Very true so why are these new benchmarks fit for purpose?
We know models are imperfect and will continue to be improved upon. Yes, it is important to test and compare different models to determine their efficacy but this needs to be done in depth exploring the full range of predictions for a wide range of geological timescales, compositions and thermal history complexity. This study is a mere snapshot.
The greatest challenge with models is the extrapolation from laboratory to geological timescales. We can only know if a model works through comparison with geological data and this is why researchers were motivated to compare different (U-Th)/He and FT models with data from borehole samples with a well constrained independent geological/thermal history which is what Naeser, (1979, 1980, 1981); Green et al., (1989) and later, House et al., (2002) attempted to do.
The discussion highlights some of the many limitations/uncertainties of (U-Th)/He and FT models that undermine the case for benchmark paths because how do you know your benchmark is a sensible reference point given the dispersion of predictions present in other models. Perhaps your benchmarks are outliers.
A final point regarding experimental design. Why choose a single composition for both AFT and AHe? – Are they representative of the most common types of apatite? The choice of using DPAR is questionable in that a DPAR of 2.05 µm can be found in apatites with between 0.02 wt% Chlorine and up to 0.8 wt% chlorine. Model outcomes would very different for some thermal histories has chlorine been used instead of DPAR.
Citation: https://doi.org/10.5194/gchron-2024-20-RC2
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